“The Union Can’t Sit Idly By”: 2013 Union Review
Bibliographic record
Abstract
In 2013, the United States and Canada both issued reports on unionization rates in their respective countries.In its annual union membership survey, the U.S. Department of Labor (2014) reported that the overall union membership in 2013 remained the same as that of 2012, with 11.3% of the workforce belonging to unions.While the highest occupational group unionization rate was among individuals working in education, training, and library occupations, the 2013 rate of 35.3% for this occupational group reflects a decrease from both the 2012 rate of 39.2% and the 2011 rate of 40.5%.An analysis of longterm unionization trends across Canada also reflected a decrease in unionization rates in the information, culture, and recreation industry, with rates dropping from 27.6% in 1999 to 25% in 2012 (Galarneau & Sohn, 2013).Other publications related to union activity in the information sector issued in 2013 include:
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".